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Every second of every day, IT generates enormous amounts of data around operational activity – system behavior, application performance, user actions, security activity, and more. Instead of viewing this data explosion as a Big Data problem, IT views it as opportunity to use Big Data solutions such as IT Operations Analytics to improve the quality of their services.

For example, 75% IT professionals surveyed recently said that they believe that IT Operations Analytics are able to transform data into relevant insights into actionable plans for improvement. I spoke with EMC CIO Vic Bhagat to describe how EMC is embracing Big Data for IT Operations Analytics to solve critical problems affecting EMC IT Operations and customers.

1. What are the biggest problems faced by IT Operations Management at EMC and how were these problems addressed before the world of Big Data?

IT generates enormous amounts of data when monitoring complex, rapidly growing and changing IT infrastructures and the applications. The challenge for IT Operations Management is to leverage this data to build an adaptive system that is more proactive, and less reactive. The more the system can learn from the data, the better it can identify variances and problems areas in a timely manner to help IT fix issues before it negatively impacts the business such as downtime or poor performance.

In the past, we relied on traditional business intelligence and data warehousing systems to gain intelligence or insight based on historical trends. Now, with analytics, we can uncover important variables and modify them to predict an outcome. And, the more data we collect at a detailed level, the more accurate we can be.

2. How does Big Data analytics change the game to address these problems more effectively?

It cuts down the time to gain insight. The most heavily used word after ‘selfie’ is now ‘data lake’. Everyone wants to build a data lake since it provides the right architecture and capabilities to cut down the cycle time in deriving newer, predictive insight, and then continuously integrating these results back into our business processes and decision-making. At EMC, we are moving away from data warehouses to a data lake architecture enabling us to not only gain faster insight, but also gain newer insight by bringing together and analyzing both structured and unstructured data.

For example, in a data warehouse you manage structured data such as part numbers, bay numbers, disk numbers, chassis numbers, and more. In a data lake you can manage all of this structured data in addition to unstructured data such as user manuals for each system and component. Let’s now apply this data lake solution to a use case – we continuously monitor the health of a customer’s infrastructure with our call home systems. We can now leverage a data lake with more data sets to not only make more accurate component failure predictions, but we can also provide the relevant information needed from user manuals to fix the problem in a timely manner so the customer experiences no downtime.

We are leveraging the entire Pivotal Big Data Suite to ingest and store all of the structured and unstructured data – Pivotal Gemfire XD, Pivotal HD, Pivotal HAWQ, and Pivotal Greenplum Database. Our Data Scientists are then able to apply advanced analytic techniques to the data they need using their choice of tools which are MadLib, R, and Python. This Big Data environment will be part of a wider business data lake strategy, where all enterprise data will be managed, accessed, and used equally by all business applications, not just IT Operations. Only a few legacy or specialized applications will standalone.

4. What benefits has EMC gained from this Big Data solution?

The benefits are enormous and can be extracted from both business and technical benefits. Building predictive models and predicting imminent system failure reduces downtime and the number of alerts and enables us to identify the real issues faster, reducing the cycle for decision making and taking corrective action. This improves our performance, productivity and value we gain from Big Data.

But we are only scratching the surface. The more we can optimize our Big Data environment so that it is elastic and accessible, the faster and more precise Data Scientists will be in solving problems. For example, we can now predict MS Exchange outages two hours in advance.

5. One of the biggest barriers to getting value from Big Data is the skills shortage. How does EMC IT Operations address this issue?

EMC had the foresight to build Centers of Excellence (COE) around the globe, producing the expertise and skills needed to transition into the realm of Data Science. We are fortunate to leverage talent within the company, but also leverage the COE to attract and acquire new Data Science talent outside the company.

6. What books are you currently reading on your Kindle or if you are still paper based like me, what books are stacked on your nightstand?

I’m Kindle based, so I read periodicals such as Techmeme and Engadget. Since we are a company that is data and digital driven, I am reading a book called ‘Leading Digital’. I want help lead this digital revolution at EMC and this book provides great examples of how digital makes significant changes in how a company operates and kills bureaucracy.

Our CMO Jeremy Burton is a visionary, always at least three steps ahead of the pack. I identified this gift early on, recalling Jeremy’s ability to excite a very calm and composed Technology Marketing team at Oracle 12 years ago through innovative ideas. I knew he was on the rise – Big and Fast. Yes, pun intended. Today, Jeremy’s vision at EMC is not only to harness Big Data to build a data-driven Marketing organization, but also to inspire other organizations to do the same in their Marketing departments through EMC’s Marketing Science Lab.

The Marketing Science Lab, built on EMC Big Data technology, provides a 360 degree view of customers in order to better understand their behavior and sentiment and improve marketing effectiveness. The Marketing Science Lab is not only accessible to EMC Marketers, but also presents itself through a highly visual dashboard application at EMC’s Executive Briefing Center in Santa Clara, CA. EMC’s Michael Foley leads the Marketing Science Lab and provides us with more insight into how this Big Data project is transforming EMC’s business and making everyone in Marketing addicted to analytics.

1. Can you describe the Big Data technology behind the Marketing Science Lab?

When I first heard of MADlib, the first things that came to my mind were the comical game and the hip-hop rapper. In the context of Big Data, MADlib is actually an open source project for Magnetic, Agile, Deep (MAD) data analysis, an orthogonal approach to traditional Enterprise Data Warehouses and Business Intelligence. The primary goal of the MADlib is to accelerate innovation in the Data Science community via a shared library of scalable in-database analytics.

One of the strong supporters and contributors to MADlib is EMC Greenplum, as MADlib is currently ported to the Greenplum Database, as well as the PostgreSQL Database. Since I am employed by EMC, I had the luxury of chatting with MADlib Architect Caleb Welton and MADlib Product Manager Gaurav Kumar over coffee in the Greenplum Break-room.

About

EMC Big Data Blog is authored by Mona Patel, Senior Manager of EMC Big Data Marketing. Having 15+ years experience analyzing data at Los Angeles Dept of Water & Power, Air Touch Communications, Oracle, and MicroStrategy, Mona is now growing her career at EMC, a leader in Big Data.